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Simulations based on noise maps for machinery location at workplace to help hazards prevention.

1. INTRODUCTION

In Europe, 22.5 million individuals suffer form hearing impairment, with 2 million being profoundly deaf. Noise induced hearing loss was the fourth most common occupational disease recognized in 2001. Reported hearing loss due to the work increased from 6 % in 1995 to 7 % in 2000. Noise levels still exceed limit values regularly in many sectors, such as agriculture, mining, forestry, manufacturing of metal and wood, electrical, textile and other processing, construction, foods and drinks industry, foundries or entertainment but also in teaching and work in catering (***, 2005).

In Romanian studies have shown that almost 40 % of population that work in industry is exposed to undesirable levels of noise and a further 10 % is exposed to excessive levels. From the last published statistical dates in Romania in 2005, 213 workers had problems of hearing loss because of noise at work and more than 300 000 are supposed to have such problems in future because of same causes. Most of these work in foods industry, metallurgy, constructions and transports and probably machine noise in industry is one of the most serious and pervasive type of noise pollution at work.

These are only few reasons for intensification the effort regarding the assessment of the risks and the control of noise level at workplace.

The most important factors affecting noise propagation in a workplace are: type of source (point or line), distance from source, materials absorption, obstacles, reflections, etc (Lara-Saenz & Stephens, 1986). Sound decreases with distance but this depends on type of source. For point source, sound intensity varies inversely with square of distance. Each time distance is doubled, dB decreases sound intensity (Bies & Hansen, 2003).

Occupiers of premises involved in the production of concrete products have responsibilities under the Norms and Directives of UE reflected in laws from their country to assess the noise exposure of their employees and, depending on the problem, to reduce the risk of hearing damage by reducing the time of exposure and controlling the noise.

It is well established that exposure to excessive noise is a risk and that prolonged exposure will result in a permanent loss of hearing and may give rise to other diseases as stress, disturb concentration and so reduce working efficiency. Thus the extent of the problem need to be reduced for benefits of both employees and employers.

The noise problem in a typical plant will depend on the arrangement of the plant, the position of the block machine and other elements. There can be implemented silencing and acoustic modification to achieve reduction in noise, such as separation of the noise source by enclosure of the block machine, use of acoustic screens, acoustic treatment of the building, rotation of employees from task to task, and so on. Another possibility is the use of ear protection, measure which is widespread in the industry, but the priority must be to reduce noise exposure by other means than hearing protection.

A solution that may be envisaged is to find, if there exist, the best configuration of the workplace such it provides a better distribution of noise in the layout of interest. This alternative is advantageous because it seems to be less expensive than the others, and sometimes is easy to be found and done.

In this paper the role of noise maps in assessment of noise at workplace is pointed out and also the benefits of constructing such maps by using a computer code based on a simple analytical approach. For example, the location of new loud machinery does not unnecessarily expose employees to noise hazards. Its emplacement can be established using simulations based on sound maps which estimate the noise level at the workplace. This represents the most efficient method to be used in order to minimize the potential impact on workers.

Noise maps can help managers to plan how to overcome noise problems in advance, to avoid unexpected and often very expensive noise control during further activity.

2. CONSTRUCTING AND USING NOISE MAPS

A very easy method to find noise hazardous areas is to use simulations based on noise maps for the workplace instead of making time consuming measurements, sometimes difficult to be done. A noise map is made up of numerous contour lines connecting points on the factory layout which have an equal noise level. Using sound measuring devices points can be found by measuring noise levels in every point of the place involved. This practical method is difficult and many errors can appear during it (Wells, 1979). Besides these, the procedure has to be repeated every time when new machinery is brought or its parameters are changed.

The present approach to plotting noise levels for different possibilities of machinery location shortens the time required for their analyses and eliminates additional costs. It can be successfully used when establishing a new machine location. In this paper for making a noise contour map a computer code based on a simple analytical method is used (Nanthavaniji, 2002). It uses data about machine noise levels and machine locations in the industrial workplace of interest.

From the contour map, potential noise hazardous areas within the facility are identified by comparing their noise levels with the permissible noise exposure limits. The contours of maximum sound level suggest the areas where the hazard is maxim and so established zones to be avoided or where workers must wear hearing protection devices. If the hazardous areas are identified adequate noise control techniques can be applied to protect workers from those areas.

The computer code we made, based on Nanthavanij analytical method, consists of the following steps and has the following assumptions (all existing machines/noise sources are considered pointed sources, and are expressed by two coordinates x, y; reflection and absorption are not considered in this approach). Initial data are: the geometry of domain, machine sound levels and positions and the ambient noise level. First a mesh of the area must be obtained. Its dimension depends on the error envisaged. Then it is necessary to convert the ambient noise level L (in dB) into sound intensity I (in W/[rn.sup.2]) using relation: I = [10.sup.(t-120) 1/10]. Then the power of sound is calculated using relation:

I = P / 4 [pi] [d.sup.2], (1)

considering that its intensity is estimated at distance d= 1m.

At each grid corner, the sound intensity is evaluated. So at location [M.sub.1] ([x.sub.i], [y.sub.i]) the sound intensity from machine situated in point [M.sub.j] ([x.sub.j], [y.sub.j]), noted [I.sub.iJ], can be determined from:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], (2)

[d.sub.ij] being the Euclidean distance between [M.sub.i], and [M.sub.j].

The combined sound intensities from all machines, noted [bar.I], can be then evaluated using formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)

For reconverting the combined sound intensity to sound level the following formula is used:

[[bar.L].sub.i] = = 10 x [log.sub.10] ([bar.I].sub.i] / [I.sub.o]), [I.sub.o] = [10.sup.-12] (4)

The noise contour map is constructed by repeating the above steps for all nodes, and by connecting points having equal sound level.

3. SIMULATIONS AND NUMERICAL RESULTS

By means of MathCAD application, based on the above method we can obtain the noise contour map for any workplace of interest, and for any configuration. Changing the place of any of the machinery presented in the area we can notice the way it influences the noise levels in the area. The following noise contour maps are made for a hypothetical situation: a hall rewrapping furniture which included four identical machines of 76 dB each of them (universal machine joinery). We study the noise map obtained when considering the following configuration of the workplace (Fig. 1), and we make simulations of two possible configurations for the case when a new machine is placed in the workplace. These configurations and the corresponding noise maps are presented in Fig.2, and Fig.3.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

Using the noise contour map individual noise exposures can be determined too.

The results in the above figures indicate the fact that in any situation, the dB levels are generally lower than 87 dB (the maximum level admitted) and no hearing devices have to be used. The potential impact on workers health would be expected to be minimal especially if the second configuration is chosen.

The present paper shows that simulations based on computational modeling of noise at work, are useful tools to study and to determine the impact of critical areas of exposure.

The importance of a noise map is reinforced by the fact that it represents a useful tool which helps the responsible for safety and health protection at work to decide on the protective measures to be taken and whom they are addressed to.

The method and the computer code have their limits and they can be improved for example by considering the three dimensional case, the absorption of sound and its reflection, and by modeling the machinery involved not only as point sources of sounds.

4. REFERENCES:

Bies, David A. & Hansen, Colin H. (2003). Engineering Noise Control: Theory and Practice--III Edition, Taylor & Francis, ISBN 0415267137

Lara-Saenz, A. & Stephens, R. W. (1986). Noise Pollution: Effects and control, John Wiley & Sons, ISBN: 9780471903253

Nanthavaniji, S. (2002). Analytical Approach for Workplace Noise Assessment, Thammasat Int. Journal of Science and Technology., Vol.7, No.3, September-December 2002, ISSN 0859-4074

Wells, R. (1979). Noise Measurements Methods, 1n Handbook of Noise Control, C .M. Harris(ed.) McGraw-Hill pp 6-1-6-12, ISBN-13: 978-0070268142

*** (2005) Report of European Agency for Safety and Health at Work, Risk Observatory, 2005, ISBN 92-9191-150-X
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Article Details
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Author:Grecu, Luminita; Grecu, Valentin; Demian, Gabriela; Demian, Mihai
Publication:Annals of DAAAM & Proceedings
Article Type:Report
Geographic Code:4E
Date:Jan 1, 2009
Words:1618
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